Claims

In deployment, 13% of sampled LLM agent responses were faulty and 37% very useful, with response quality improving over weeks of use

Claim · All claims
Evidence · 1 study · causal r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2029: tool and model accuracy changes quickly

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q2 i? Human evaluation of 284 randomly sampled LLM responses found 13% faulty and 37% likely very useful, with faulty proportions decreasing in later weeks. → Graf 2026

Evidence

Graf 2026

Graf, L., Bassner, P., Anzinger, M., Dietrich, F., Krusche, S., & Poquet, O. (2026). Interactive learning dashboards: rethinking learning visualisations as engagement tools. Education and Information Technologies. https://doi.org/10.1007/s10639-026-14082-1

q2 · i? · causal · r2

System evaluation of agent response sensibility: 284 randomly sampled responses rated by humans. In the first two weeks 37% were faulty and only 27% very useful, indicating students learned what the chatbot was useful for.

"Overall, 13% of the randomly sampled LLM responses were labelled as faulty (not fully matching the request by human common sense or containing false or misleading claims). 37% of them were rated as likely very use-ful for the student."

Discussion

Page metadata
Field Value
type claim
id llm-agent-response-quality-evaluation
title In deployment, 13% of sampled LLM agent responses were faulty and 37% very useful, with response quality improving over weeks of use
description In deployment, 13% of sampled LLM agent responses were faulty and 37% very useful, with response quality improving over weeks of use
status review
evidence_strength weak
newest_evidence 2026
recheck_by 2029
generated by process:wiki-ingest on 2026-10-11
trust unverified — no one has confirmed this page's content
sources 1 — graf-2026

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